Distributed Tracing app overview

Latest Dynatrace

Distributed Tracing Distributed Tracing enhances Dynatrace abilities to analyze and filter trace data at both the request and span levels. With advanced filtering options, such as facets and the grouping function, you can easily explore and pinpoint issues. In addition, your selection is preserved across interactions, enabling you to drill down to the single trace information, and to identify the root cause and prevent failures in your environments.

  • In the Distributed Tracing welcome view, you can get started discovering the app and getting data into Dynatrace. Alternatevely, you can add trace data at any time by selecting Traces and choosing a source. Follow the in-product guidance to continue the configuration for the selected source.
  • The default view Explorer contains all the user-interface elements to analyze your trace data.

Requests and spans

A distributed trace is a collection of spans representing a request's journey through a distributed system.

  • The request is the call initiated by a user or system to perform a specific task. It interacts with various services and components within the distributed system. To view trace data created in your environment in response to an external request, select Requests.
  • Spans are individual operations representing each request interaction with the distributed system. To view all trace data by single operations, select Spans.

Filter field

By entering a query in the filter field, you can quickly build DQL-based filtering options.

"Kubernetes namespace" = prod AND Endpoint = /cart/* AND "Response time" >= 5s

You can narrow your results by focusing on a timeframe. Select Refresh to get the latest result for the selected timeframe.

The filter field is automatically modified when you apply other filtering selections, such as facets. To update the results after you change the filter field query, select Update.

Use cases

  • Get results for any key-value pair.
  • Visualize and edit your filtering selection.

Charts

The charts allow you to view your trace data trends and distribution. You can also hide or show the chart card again at any time.

When you hover over the chart and select an area, the filter field and results are automatically updated to focus on the selected portion of the trace data.

Distributed Tracing charts

The following table compares the Timeseries and Histogram charts.

Timeseries

Histogram

X-axis

Time intervals 1

Response time intervals

Y-axis

Frequency of data points (left-hand side) and response time (right-hand side)

Frequency of data points

Important statistical factors

The legend lists dedicated views for percentiles, averages, and successful and failed requests. Choose an option to view the related trends.

Percentiles and averages are marked with contrast-color vertical lines.

Use cases

Understand how trace data changes over time and identify trends and cyclic behaviors.

Visualize your data's distribution, identify patterns, and spot outliers.

1

Granularity depends on the selected timeframe.

Facets

Facets are quick filters for trace data. They correspond to span attribute key-value pairs detected in your environment and are grouped by facet categories. The most important DQL field IDs are grouped by default in predefined categories. You can define new facet categories and new facets for attributes that are important to you. Each facet category displays the most frequently detected attributes for the current filtering selection.

UI element

Scope

Show facets

Manage all facets of your environment. Select/deselect a facet to modify the facet list.

Group by, edit, or hide a facet.

Modify the filtering selection.

Use cases

  • Add new facets to better catalog your trace data.
  • Select facets from the facet list to filter data by them. The filter field is automatically modified according to your selection. Make sure to select Update.

Table results

The table lists the latest 1000 records for the selected timeframe that match the filtering options you applied. The table data is available as a list ( ) or grouped by attributes ( ). You can manage columns to display only the attributes you're interested in and exclude noise.

UI element

Scope

<column value>

Filter trace data by a column value.

Copy the DQL statement or the DQL API call.

Download the visible table data.

Use cases

  • Compare records and their different attribute values.
  • Filter trace data by a result by selecting the table result. The filter field is automatically modified according to your selection. Make sure to select Update.
  • Reduce noise by hiding unnecessary columns from the table or deselecting an attribute.

Group by

Analyze predetermined important dimensions, such as request count, failure, and percentile contribution, by combining up to 3 attributes that matter the most to you. To group your records by attributes,

  • Go to the table and select Group by:. Then select/deselect the attribute you're interested in.
  • Go to the facet list and select > Group by for each attribute key.

Single trace perspective

The single trace perspective offers a detailed view of the trace spans.

  • The waterfall list on the left-hand side contains the trace spans, ordered by sequence. Each span is related to a service and has a corresponding duration bar. Spans associated with the same service are of the same color. You can understand the sequence and correlation of spans by observing the size and position of the duration bar.

    UI element

    Scope

    Search name, endpoint, service, or attribute

    Enter a value to highlight the spans matching your search.

    Name

    View all spans for the selected trace.

    <span name>

    View the subsequent span in the trace execution.

    <span name>

    View attributes for the span in the details panel.

  • On the right-hand side, you can explore and search for attributes for the selected span. Enter a value in the Search details field to view only key or value results matching your search.

To access the single trace perspective, go to the table row of the trace you're interested in and select the trace start time. The single trace perspective opens in the bottom half of the page.

Use cases

Focus on the analysis of a single trace.